Abstract
The challenges of the modern world accelerated the development of many fields of technology, including rehabilitation robotics. The focus of the robot-aided motor therapy is put on providing remote, home treatment. According to the conducted research, also, functional kinesiotherapy is a leading trend for the future. Therefore, designing a mechatronic device enabling such a workout is needed. The presented study is based on a concept of an upper extremity exoskeleton with free degrees of freedom. However, it is applicable for any exoskeleton with non-controlled joints. The paper corresponds to the problem of a control system for a not fully controlled robot; especially, as the mass parameters of the user’s limb remain unknown. Investigated prediction control is based on a recurrent neural network model of the system. The dynamics simulations are all performed without the usage of a physical device. Nevertheless, the outcomes of the trials prove, that such a control approach is suitable for the exoskeletons with free degrees of freedom. The results may be the base to adjust basic parameters of the neural networks used for similar applications.
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Falkowski, P. (2022). Predicting Dynamics of a Rehabilitation Exoskeleton with Free Degrees of Freedom. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2022: New Solutions and Technologies for Automation, Robotics and Measurement Techniques. AUTOMATION 2022. Advances in Intelligent Systems and Computing, vol 1427. Springer, Cham. https://doi.org/10.1007/978-3-031-03502-9_23
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